Causality is the relationship between an event (the cause) and a second event (the effect), where the second event is understood as a consequence of the first.

A startup is a human institution designed to create a new product or service under conditions of extreme uncertainty. Uncertainty is the essence of a startup. A startup operates in an uncertain environment: both the problem to be solved and the product to build are unknown. This is why learning is the vital function of a startup. 

Learning means updating our theories about reality, and these theories are expressed as cause-effect relationships. The problem is that our understanding of causality is often broken, and since our decisions are all influenced by our assumptions on causality, they have the potential to sway them.

In this post I investigate the problems of cause-effect relationships and show how we can overcome this obstacle.

The problem with causality

Learning is all about understanding why things happen and why some events lead to other events. Learning is about understanding the casual link between things. 

But this casual link doesn’t exist in reality; it isn’t a property of things. We cannot perceive cause and effect, but as the Scottish philosopher David Hume once said, we develop a habit of mind where we come to associate two types of object and event, always contiguous and occurring one after the other. Contiguity and succession are what we call causality.

Now, we infer causality from sensory information, prior experience and innate knowledge. And here come our problems:

Limited information - Only limited, often unreliable, information is available; in complex situation, many interdependent factors affect outcomes. Sometimes we ignore how factors are linked between themselves, sometimes we ignore what factors affect a situation: we usually deal with partial information;

Limited capacity - Human mind has only limited capacity to evaluate and process the information that is available. Usually, our prior experience and knowledge teach us what to look at;

Attribution errors - Human beings have a tendency to over-value dispositional explanations for the observed behaviors of others while under-valuing situational explanations for those behaviors. For example, we are likely to attribute our success to our insights and skills while downplaying others’ success to good luck or other external factors.

How to overcome these obstacles?

David Hume suggested what he calls mitigated skepticism: since we all have limited experience, our conclusions should always be tentative, modest, reserved, cautious. Nonetheless, anyone “sensible of the strange infirmities of human understanding” should also strive for overcoming these obstacles, and here is my advice. 

Data-informed - Make data-informed, not data-driven decisions. Data give you half the picture: they measure the past, and cannot predict the future. Treat data with caution: you might have measured the wrong thing, you might have measured the right thing in the wrong way. 

Test your assumptions - When too much uncertainty prevents you from a full understanding of your problem, you have only one choice: test your hypotheses. In science, this is known as the scientific method. If you think you’re doing right, test your assumptions. Do it.

Stay flexible - When there is too much uncertainty, flexibility is the key to success. Don’t make long term commitments that harm your capability to adapt to a fast changing environment. Napoleon would order his troops to stay at most 1-day march distance so that they were in mutually supporting positions and able to come to the aid of each other in the event of concentration for battle or to ward of superior forces. Since the battle plan was formulated only when enemy’s intentions were clear, this formation gave the Frenches the flexibility to gain a strategic advantage over their enemies.

I don’t want to encourage risk-taking behavior. In 218 BC, Hannibal invaded Italy by land across the Alps. The task was daunting to say the least. Nobody thought it would be possible. But Hannibal knew it was possible, and did it. Intuition is a highly developed pattern recognition process. It have to be trained, and nothing can train intuition like experience. 

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Have you ever followed your gut instinct when odds were against you? Let me know your experience with a comment.

If the man of action, in Goethe’s phrase, is without conscience, he is also without knowledge: he forgets most things in order to do one, he is unjust to what is behind him, and only recognises one law, the law of that which is to be. So he loves his work infinitely more, than it deserves to be loved; and the best works are produced in such an ecstasy of love that they must always be unworthy of it, however great their worth otherwise.

(F. Nietzche - “On the Use and Abuse of History for Life”)

Recently, I have been reading an article by Neal Stephenson on innovation starvation. The author speaks about the inability of Western societies to execute on big things. One point that made me think is the thesis that too much information is killing innovation. It is something I have thought about lately, so I want to share my thoughts with you.

Can information kill creativity?

We live in a world where anyone can easily access information; better access to information has surely improved our life increasing our efficiency. But excited by the power information gave us, we haven’t take any attention to the unintended consequences of having too much available information.

My thesis is that too much information, when not properly managed, can kill creativity, and consequently, innovation, by affecting our ability to take risks.

What is creativity?

According to the Merriam-Webster dictionary, creativity refers to the ability to make or bring into existence something new. There is a lot of psychological research about what drives creativity – and also about the exact definition of what creativity is – but I don’t want to bother you, so we will stick to what common sense tells us.

If we define creativity as the ability to bring into existence something new, we must hold that if an individual wants to create something new, she must accept the risk that she might fail. Newness is intrinsically risky, because if something is really new, we don’t have anything telling us that we will succeed. It’s quite obvious that if we don’t accept such a risk, we can’t do creative things. We can do small improvements to existent things (that isn’t so bad, by the way), but we can’t make big, disruptive innovation.

So, creativity is deeply linked to the ability of individuals to accept the risk of failure. I want you to focus on this point because it is the keystone of my thesis. Since creativity is deeply linked to the ability of individuals to accept the risk, it goes without saying that anything which modifies our risk propensity modifies also our creativity.

So far we have understood that when our risk propensity lowers, we are unwilling to take the unknown road for the known one; but how does this affect creativity?

This problem is what in optimization theory is called the local maximum problem (or for the computer scientists between us, the hill climbing problem). Simply put (dear maths, don’t hold it against me), local maxima occur when you try to solve a problem step by step and find a solution that seems optimal, but it is optimal because you are considering only a small subset of the original problem. When something holds you from looking for alternative solutions, your creativity surely suffers.

How can information modify our risk propensity?

Information can modify our risk propensity in several ways; in the following I will discuss two ways information can affect our risk propensity: partial information and social proof.

The available information depicts the effects at the expense of the causes. Most of time, you only know the effects of decisions, while causes remain obscure to you. This is what I call partial information: you have a partial knowledge of the problem space.

Now, a wise man would acknowledge this situation and says: “Hey, this is what I have. I will use it but with the awareness that this is only partial knowledge”. A wiser man would further say: “I don’t mind, I will follow my instinct”.

But typically what we do is to believe in ineluctable certainty and transform that partial knowledge in a full, absolute knowledge. This is where you start avoiding risks; since there is no certainty, we build the illusion of a risk free world: we start taking small steps, the risk free ones, climbing the hill and forgetting the mountain, shaping our world as a risk-free world. We simply negate risks.

The availability of partial information generates the illusion that risk doesn’t exist. Since risk does not exist, how do you call people that take pointless risks (Take the word for yourself)? This is where social proof happens. As social beings, we are constantly responsive to the activities of others. When we face a situation in which we don’t know what to do, we are used to look for clues in others’ behaviors to make our choice. With all the social media available nowdays, we are being constantly flooded with opinions by others. What happens is that all these things might discourage us from continuing on big, bold projects. To say as Nietzche,

“He has lost or destroyed his instinct ; he can no longer trust the “divine animal” and let the reins hang loose, when his understanding fails him and his way lies through the desert. His individuality is shaken, and left without any sure belief in itself; it sinks into its own inner being, which only means here the disordered chaos of what it has learned, which will never express itself externally, being mere dogma that cannot turn to life”

How can we defend ourselves from too much information?

Information is not bad at all; it is bad only in the measure it starts affecting our risk propensity. Here are some simple tips you can use to control how information affects your behavior:

1. Understand that information is, at the best, partial

It is impossible to get a complete knowledge about an event. You only get partial information. What is worse, you don’t know what information you are missing. So, learn what you can learn after a critical assessment and leave a small space for your gut instinct.

2. Follow your gut instinct

Innovation requires you to fail. If you have a hunch that the gamble might pay off in the long run, place that bet. Life is too short to brood over things; trying is the best way to learn new things (of course, you must also minimize the negative effects of failing and setting your mind in learning mode).

3. Know thyself

Organize the chaos inside you and start thinking back to yourself, to your own true necessities, and letting all the sham necessities go.

I want to conclude with the opening quote from Nietzche. Remember that every man of action is without conscience and a bit of oblivion is needed to get things done.

And you? Have you ever been in situations where too much information were holding you back? How did you overcome them? Let me know in the comments.

Programmers are in a race with the Universe to create bigger and better idiot-proof programs, while the Universe is trying to create bigger and better idiots.  So far the Universe is winning.

(Rich Cook)

Computer programming is fun. This is the only truth. Don’t trust who says that it is boring. Or better, just feel sorry for her, because two are the reasons: either she let others mortify her passion or she got into the job just for money. Since this blog is all about passion, I will speak now about the latter.

Programming job pays. In Italy it is one of the few industries in which we can still find a job as a fresh graduate. This means that tons of people are coming into the job just to escape the brutal sickle of unemployment. There is nothing wrong to me, but I would advice those people that programming is just for who loves it. Certain tasks are really boring; much of today’s software development is really glueing, that is linking together libraries that do the work for you. Then, your company gives you a database, and you have to write those silly pieces of code that do Create, Read, Update, Delete. If you are lucky. Otherwise, you will likely be forced to use a CRUD generator and link code generated by it. Stop. There is nothing inherently wrong with this: we live in a world of limited resources, and we must work efficiently and effectively. This is the raison d’être of Corporate IT. If you don’t love programming, this will likely kill the fun. So, where is the fun?

We could ask several thousands of true programmers, and all of them will say that the fun is in the creation. A programmer starts from nothing and creates something. He is the agent the transforms the not-being into being. He received a gift, the gift of God:

Why is programming fun? What delights may its practitioner expect as his reward? First is the sheer joy of making things. As the child delights in his mud pie, so the adult enjoys building things, especially things of his own design. I think this delight must be an image of God’s delight in making things, a delight shown in the distinctness and newness of each leaf and each snowflake.

(Frederick P. Brooks, Jr.)

It is that sense of creation that makes programming meaningfull, and we should never forget this truth: we create. So, the antidote for the sense of boredom that kills the fun of programming is simply: have passion.